The success of proteomics research depends on the ability to reliably identify and quantify any protein or set of proteins present in a biological system. However, because typical biological samples contain a complex mixture of proteins and other components, analysis of such samples using mass spectrometry is not straightforward.
Certain tandem mass spectrometry (“MS/MS”) systems have been developed to detect proteins in biological samples. In this approach, the sample is extracted to recover the proteins, optionally through the use of fractionation by chromatography or SDS-PAGE or other separation techniques. The protein fractions are subjected to proteolytic digestion to obtain component peptides, which are desalted and concentrated. The resulting peptide mixture is subjected to an initial mass spectrometry analysis, designated MS1. The MS1 spectrum depicts the intensity of signal, which corresponds to the amount of the peptide present in the sample. Ions of interest in the MS1 spectrum are selected and subjected to a second mass spectrometry event, induced by collision-induced dissociation (CID), which results in fragmentation of the selected peptide to yield a second mass spectrum (MS2) with sufficient information to permit identification of the peptide by comparison to available databases. However, because such MS/MS analysis systems are limited by the ability of the instrument to detect a peptide of interest in the MS1 spectrum, only proteins of relatively high abundance are detected. Furthermore, even if a particular protein is identified, the intensity of a particular m/z ratio in an MS1 spectrum does not permit quantitation absent some internal standard.
The quantitation issue has been addressed in alternative systems through the addition an internal standard having a known m/z relationship with the protein or peptide of interest. Quantitation is achieved by comparing the relative intensities of the internal standard, which is added to the sample in a known amount, and the target protein or peptide. Alternatively, relative amounts of proteins in mixtures can be determined by comparing the relative intensities of peptides derived from two different samples.
Currently, “shotgun” mass spectrometry (MS), paired with stable isotope labeling of proteins or peptides, is an attractive and widely applied approach for quantitative proteomics. A variety of methods for the incorporation of stable isotope labels into proteins have been reported, and include metabolic labeling (e.g., stable isotope labeling with amino acids in cell culture, or “SILAC”), chemical derivation of proteins (e.g., isotope coded affinity tag, or “ICAT”) or peptides (e.g., isobaric tag for relative and absolute quantitation (“iTRAQ”), tandem mass tag technology (“TMT”), isotope coded protein labeling (“ICPL”)), and enzymatic labeling of peptides. See, e.g., Colzani, M. et al., Mol. Cell. Proteomics (2008) 7.5:927-937; Hanke, S. et al., J. Proteome Res. (2008) 7:1118-1130; Thompson, A. et al., Anal. Chem. (2003) 75:1895-1904; Ross, P. L. et al., Mol. Cell. Proteom. (2004) 3:1154-1169. A review of various mass spectrometry-based analytical platforms is provided by Doman, B., et al., Science (2006) 312:212-217.
In the SILAC approach, the internal standard is a peptide identical to the peptide of interest, which has been modified with specific isotopic substitutions that alter its m/z ratio but not its chromatographic or chemical behavior. For example, the internal standard is generally a heavy isotopic form of the desired protein (i.e., containing rarer, heavier isotopes such as 15N, 18O, and/or 13C). The heavy standard is added to the initial extract and is carried along with the peptides or proteins of interest through the sample preparation and analysis process. The peak generated in MS1 for the peptide of interest is compared to the corresponding peak for the heavy internal standard to quantify the target peptide. In similar methods, samples are spiked with heavy isotopes at later points in the sample preparation process; for example, QconCAT uses concatenated peptides, and the AQUA® method includes peptide standards and H218O-digestion of protein standards. Alternatively, the relative amounts of proteins in mixture can be determined by differentially labeling the proteins with stable isotopes. Colzani et al. describe a more complex form of the SILAC method involving two isobaric forms of the heavy protein.
While such shotgun MS-based quantitative proteomics platforms have been used to quantify significant fractions of proteomes, the sensitivity, accuracy or quantitation, and reproducibility of the approaches do not meet the demands of many proteomics studies. To address these issues, recent efforts have focused on developing MS-based methods to monitor specific sets of proteins. Such proteomics platforms are expected to play important roles in clinical applications as well as in basic science studies where sets of proteins need to be consistently quantified under different conditions. One particularly promising targeted approach involves the use of selected or multiple reaction monitoring (“SRM” or “MRM”) mass spectrometry of specific sets of parent and fragment ions (transitions) for each targeted peptide using triple quadrupole (QQQ) instruments. Other related methods involve the use of inclusion lists with high mass accuracy scanning mass spectrometers, such as the LTQ Orbitrap, to focus MS analysis on predetermined precursor ions.
However, these advanced methods still face limitations. For instance, although inclusion list methods can provide enhanced sensitivity and reproducibility, the target precursor ion must still be detectable in an MS1 survey scan for a fragment ion spectrum (MS2 or MS/MS) to be generated. This problem becomes critical when the targeted peptides are of low abundance in biological samples with high complexity and dynamic range. The SRM method is a sensitive, reproducible, and quantitative targeted approach, but its application is limited by a prerequisite assay optimization process. Such optimization typically involves selecting the most suitable transitions for each targeted peptide, and determining optimal collision energy settings and liquid chromatography (LC) retention time characteristics for each target peptide. In addition, quantification is typically determined based on a limited number of transitions per peptide made on QQQ instruments with modest mass accuracy and resolution; thus, the accuracy of the measurement may be compromised by chemical noise and co-eluting ions, especially in complex samples.
Existing reporter ion-based isobaric tagging reagents (e.g., iTRAQ or TMT) used for MS2-based quantification are limited by: (1) the need to detect reporter ions in the low mass range, which limits the range of suitable instruments; and (2) potential interference by co-eluting peptide ions with similar m/z values.
Other MS2-based quantitative proteomics approach have been described that use peptide-specific fragment ions for quantification. However, in these approaches an enlarged precursor isolation window (e.g., 10 m/z units) is needed to cover the m/z range of both light and heavy isotopically labeled precursor peptides for simultaneous CID and subsequent quantification (based on y-ions). While the use of multiple fragment ions for quantification improves accuracy, this advantage is muted by the inclusion in the broad window of unrelated peptide ions and chemical noise in the collision cell which may interfere with quantification.
Koehler et al. reported an approach for quantifying isobaric peptides during MS2. Koehler, C. J. et al., J. Proteome Res. 2009, 8(9), 4333-41. In that study, the isobaric peptides were generated by chemical labeling of LysC digested peptides with both succinic anhydride (Δ0 or Δ4) at the N-termini and 2-methoxy-4,5-dihydro-1H-imidazole (Δ4 or Δ0) at the C-terminal lysine residues, respectively. Although the isotopically labeled isobaric peptides proved useful for quantification, the approach is restricted to peptides ending with lysine and requires two amine-based labeling steps. Most importantly, protein abundance is only semi-quantitatively estimated from Mascot scores rather than from direct measurement of fragment ion intensities.
Thus, although there are a variety of available strategies for effecting identification and quantitation of proteins and peptides in complex samples, there remains a need for a proteomics platform which efficiently identifies subject peptides and proteins, and/or generates reproducible and accurate quantitative measurements in a high throughput manner, even at low target concentrations.